function_app/bp_form_extraction_with_confidence.py [86:142]:
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)


# Setup Pydantic models for validation of LLM calls, and the Function response itself
class LLMExtractedFieldsModel(LLMResponseBaseModel):
    """
    Defines the required JSON schema for the LLM to adhere to. This can be used
    to validate that the LLM's raw text response can be parsed into the format
    that is expected by downstream processes (e.g. when we need to save the data
    into a database).

    This class inherits from LLMResponseBaseModel and sets a description and
    example for each field, allowing us to run `model.get_prompt_json_example()`
    to generate a prompt-friendly string representation of the expected JSON
    that we can provide to the LLM.
    """

    account_no: str = Field(
        description="The account number to be opened.",
        examples=["1189234623462"],
    )
    branch_ifsc: str = Field(
        description="The branch IFSC.",
        examples=["SWTK892374"],
    )
    title: str = Field(
        description="The Title of the account holder.",
        examples=["Mrs"],
    )
    first_name: str = Field(
        description="The first name of the account holder.",
        examples=["John"],
    )
    last_name: str = Field(
        description="The last name of the account holder.",
        examples=["Smith"],
    )
    day_of_birth: str = Field(
        description="The day of birth of the account holder.",
        examples=["31"],
    )
    month_of_birth: str = Field(
        description="The month of birth of the account holder.",
        examples=["12"],
    )
    year_of_birth: str = Field(
        description="The year of birth of the account holder.",
        examples=["1985"],
    )
    pan: str = Field(
        description="The PAN of the account holder.",
        examples=["SKIFP1234K"],
    )
    customer_id: str = Field(
        description="The Customer ID of the account holder.",
        examples=["128740928"],
    )
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function_app/extract_blob_field_info_to_cosmosdb.py [64:120]:
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)


# Setup Pydantic models for validation of LLM calls, and the Function response itself
class LLMExtractedFieldsModel(LLMResponseBaseModel):
    """
    Defines the required JSON schema for the LLM to adhere to. This can be used
    to validate that the LLM's raw text response can be parsed into the format
    that is expected by downstream processes (e.g. when we need to save the data
    into a database).

    This class inherits from LLMResponseBaseModel and sets a description and
    example for each field, allowing us to run `model.get_prompt_json_example()`
    to generate a prompt-friendly string representation of the expected JSON
    that we can provide to the LLM.
    """

    account_no: str = Field(
        description="The account number to be opened.",
        examples=["1189234623462"],
    )
    branch_ifsc: str = Field(
        description="The branch IFSC.",
        examples=["SWTK892374"],
    )
    title: str = Field(
        description="The Title of the account holder.",
        examples=["Mrs"],
    )
    first_name: str = Field(
        description="The first name of the account holder.",
        examples=["John"],
    )
    last_name: str = Field(
        description="The last name of the account holder.",
        examples=["Smith"],
    )
    day_of_birth: str = Field(
        description="The day of birth of the account holder.",
        examples=["31"],
    )
    month_of_birth: str = Field(
        description="The month of birth of the account holder.",
        examples=["12"],
    )
    year_of_birth: str = Field(
        description="The year of birth of the account holder.",
        examples=["1985"],
    )
    pan: str = Field(
        description="The PAN of the account holder.",
        examples=["SKIFP1234K"],
    )
    customer_id: str = Field(
        description="The Customer ID of the account holder.",
        examples=["128740928"],
    )
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